O. Marelli

53 papers receiving 638 citations

Peers

O. Marelli
Comparison fields: 5 of 98
  • Endocrine and Autonomic Systems 47
  • Immunology 124
  • Molecular Medicine 27
  • Endocrinology, Diabetes and Metabolism 84
  • Hematology 47
Replace Lukasz Japtok with:
Lukasz Japtok Germany
Guohu Di China
Peter Keng United States
Jia‐Yu Zhong China
Min Fang China
Xiao-Pei Gao United States
Haiting Wang China
Changsen Wang Canada
Xunbao Duan United States
Kazuhiko Matsuno Japan
O. Marelli relative to Lukasz Japtok Germany Lukasz Japtok's profile →
Citations per field
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Citations per year

Countries citing papers authored by O. Marelli

Since Specialization
Citations

This map shows the geographic impact of O. Marelli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by O. Marelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites O. Marelli more than expected).

Fields of papers citing papers by O. Marelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by O. Marelli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by O. Marelli. The network helps show where O. Marelli may publish in the future.

Co-authors

The 25 scholars most cited alongside O. Marelli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with O. Marelli Line = papers co-authored together O. Marelli links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201957
2 199753
3 201836
4 200736
5 198635
6 200632
7
Hematoporphyrin derivative rescue from toxicity caused by chemotherapy or radiation in a murine leukemia model (L1210).
198430
8 201929
9 199828
10 200223
11 201421
12 199020
13
Dacarbazine-induced immunogenicity of a murine leukemia is attenuated in cells transfected with mutated K-ras gene.
199720
14 198119
15 201318
16 199018
17
Ultradian chronomodulation by melatonin of a Placebo effect upon human killer cell activity.
198717
18 201815
19
Chemotherapy and immunotherapy of L1210 leukemic mice with antigenic tumor sublines.
198112
20 201411

About O. Marelli

O. Marelli is a scholar working on Molecular Biology, Immunology, Oncology, Radiology, Nuclear Medicine and Imaging and Hematology, having authored 55 papers that have together received 662 indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (13 papers), Chronic Lymphocytic Leukemia Research (7 papers), Chronic Myeloid Leukemia Treatments (7 papers), Lymphoma Diagnosis and Treatment (6 papers), Immunotherapy and Immune Responses (6 papers), Immune Cell Function and Interaction (5 papers), Neuroendocrine Tumor Research Advances (5 papers) and Photodynamic Therapy Research Studies (4 papers). The work is most often cited by research in Endocrine and Autonomic Systems (47 citations), Immunology (124 citations), Molecular Medicine (27 citations), Endocrinology, Diabetes and Metabolism (84 citations) and Hematology (47 citations). O. Marelli has collaborated with scholars based in Italy, United Kingdom and France. Frequent co-authors include D. Lattuada, Gianfranco Canti, A Nicolin, Paola Franco, Donatella Lattuada, C. Corradini, Luisa Ricci, F. Fraschini, Noemi Tonna and Carla Perego. Their work appears in journals such as Cancer Letters, Journal of Neuroimmunology, International Journal of Immunogenetics, The Journal of Immunology and Cancer Immunology Immunotherapy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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